MIM Overview | How does ChannelMix's Modeling Engine work?

Version 2022.4.1

The upgraded Plan Performance tabs of your dashboards are powered by a machine learning model, an algorithm that examines large amounts of historical data to find relationships between variables and a target. It can then use those relationships to make predictions about future performance. 

Because it's automated, the model can consume extremely large amounts of data very quickly and uncover patterns faster than an entire team of human analysts could. 

The model does this by "training" itself - constantly updating and optimizing its understanding of the relationship between variables with each new piece of data it encounters. 

Marketing & Media Mix Model and Machine Learning

In the case of ChannelMix's Marketing & Media Mix Model, we use a supervised learning model. 

We provide the model with specific inputs (how much was spent on each marketing channel) and a specific output (leads, sales, or revenue generated) and ask the model to find the rules or patterns that link those two sides. 

For example, the model might reveal that...

• Spending $10,000 on Channel A leads to $1000,000 in new revenue
• Spending $5,000 on Channel B has a positive effect on revenue for the next 6 days
• Spending on Channel C starts becoming less effective after $20,000 has already been spent

And that's just a tiny, tiny sliver of the patterns that might be uncovered by the model. The model can make predictions for multiple combinations of channels at multiple levels of spending. Or put another way, you can use the model to make predictions.